DOCSLIB.ORG

Understanding Quantitative Genetics in the Systems Biology Era Mengjin Zhu, Mei Yu, Shuhong Zhao

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Understanding Quantitative Genetics in the Systems Biology Era Mengjin Zhu, Mei Yu, Shuhong Zhao Int. J. Biol. Sci. 2009, 5 161 International Journal of Biological Sciences 2009; 5(2):161-170 © Ivyspring International Publisher. All rights reserved Review Understanding Quantitative Genetics in the Systems Biology Era Mengjin Zhu, Mei Yu, Shuhong Zhao Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricul- tural University, Wuhan 430070, P. R. China Correspondence to: Shuhong Zhao, Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education, Huazhong Agricultural University, Wuhan 430070, P. R. China; Tel: +86-27-87284161; Fax: +86-27-87280408; E-mail: [email protected] Received: 2008.12.03; Accepted: 2009.01.21; Published: 2009.01.27 Abstract Biology is now entering the new era of systems biology and exerting a growing influence on the future development of various disciplines within life sciences. In early classical and mo- lecular periods of Biology, the theoretical frames of classical and molecular quantitative ge- netics have been systematically established, respectively. With the new advent of systems biology, there is occurring a paradigm shift in the field of quantitative genetics. Where and how the quantitative genetics would develop after having undergone its classical and mo- lecular periods? This is a difficult question to answer exactly. In this perspective article, the major effort was made to discuss the possible development of quantitative genetics in the systems biology era, and for which there is a high potentiality to develop towards "systems quantitative genetics". In our opinion, the systems quantitative genetics can be defined as a new discipline to address the generalized genetic laws of bioalleles controlling the heritable phenotypes of complex traits following a new dynamic network model. Other issues from quantitative genetic perspective relating to the genetical genomics, the updates of network model, and the future research prospects were also discussed. Key words: systems quantitative genetics; definition; dynamic network model; prospect 1. Introduction There is a trend in life sciences development that, the advent of systems biology would inevitably give as a discipline, the development of Biology depends explosive birth to a diversity of new fields being on accumulating and assimilating the new knowledge dressed up with a "systems" prefix as the "molecular" in other various disciplines within life sciences, and in in the molecular era. reverse, provides a common time division of their Quantitative genetics was founded, in evolu- historical stages. From Classical Biology to Molecular tionary terms, by the originators of the modern syn- Biology, various life sciences have been led into the thesis. This field is a relatively independent branch of molecular era, e.g., the emergences of the molecular life sciences but the one increasingly applied in a wide biology-related disciplines such as molecular nu- spectrum of scientific disciplines such as evolution, triology, molecular immunology, molecular ecology, animal and plant breeding, behavioral genetics, con- molecular evolution and phylogenetics. Now, the servation biology, medical genetics, ecology, anthro- time has come for Biology to enter the era of systems pology and psychology [4-11], which particularly has biology after having undergone its classical and mo- played a crucial role in relieving the worldwide fam- lecular periods [1-3], which is exerting an increasing ine through genetic improvement of the productivity influence on the transformation of life sciences from a of the agricultural animals and crops. It is anticipated reductionist to a systemic paradigm. It is believed that that new development in quantitative genetics will be http://www.biolsci.org Int. J. Biol. Sci. 2009, 5 162 of great benefit to various other branches of life sci- and soft inheritance, the genetic information flow ences. An outline of near 100 years' published litera- from DNA polymorphisms to phenotypic variations tures in this field had documented that the historical is not linearly dispersed in living organisms. This de- development of quantitative genetics was rough run- termines that there is no complete congruence be- ning after that of Biology. In its history, the quantita- tween DNA and phenotype. It is very necessary to tive genetics had gone through the first and second open the black box between genes and phenotypes. developmental stages, i.e., the classical and molecular In fact, the phenomena that heritable component quantitative genetics, respectively [12] [13], which, in of phenotypic variation was aroused without DNA despite of having partial overlap, were as expected sequence changes have been proven to have a fre- corresponding to the classical and molecular periods quent occurrence at both cellular and organism levels of Biology. It could be concluded that Biology has also [16-18], which reveal that the variome at the DNA provided the discipline background for the develop- level cannot provide a full elucidation of the heritable ment of quantitative genetics. After the long devel- phenotypes. As suggested by Johannes et al. (2008), opment from classical to molecular quantitative ge- more effort should be given to capture the potentially netics, it might be timely for quantitative genetics to dynamic interplay between chromatin and DNA se- be brought into the third developmental stage in the quence factors in complex traits [19]. There are also coming era of systems biology. many evidences, more accumulated in plants, that non-Mendelian genetic factors modifying the DNA 2. Proposal of systems quantitative genetics can be inherited. On many occasions, quantitative 2.1 Background and definition genetic investigations of target traits only from DNA polymorphisms is no longer absolutely appropriate, Our knowledge of the classical and molecular though it is still debated how important the non-DNA quantitative genetics has undergone a striking expan- sequence variation is in controlling the inheritance of sion in the last century. The classical quantitative ge- phenotypes. Up to date, some pilot work to address netics considers a black box to reveal the holistic this subject has already been undertaken, in which the status of all genes associated with the variation of molecular information mediated between DNA and investigated traits by complicated statistical methods phenotype such as RNA splicing, proteins, metabo- [14]. The subsequently (but partially overlapped in lites or their combinations has been brought into the time) established molecular quantitative genetics new research area of quantitative genetics [20-23]. mainly focuses on evaluating the coupling association How to weigh and integrate the contribution of bio- of the polymorphic DNA sites with the phenotypic logical molecules at different levels and their interac- variations of quantitative and complex traits, as well tions to the heritable component of phenotypes is a as dissecting their genetic architectures, but which new exciting challenge brought to us, of which both never pays attention to the details of how genetic in- classical and molecular quantitative genetics are in- formation is transcriptionally and translationally capable. processed. The absence of the inside functional in- Further development of quantitative genetics formation prevents a definitive identification of the based on the systems biology thinking would provide gene(s) underlying the control of target traits, which an alternative solution to this challenge. Now it is usually requires a subsequent validation of the gene perhaps timely for quantitative genetics to enter into function in more future generations of the same its third developmental stage. Here, as coined by us population or other different populations, or quanti- previously [24], we propose to use the term "Systems tative complementation test. In living organisms, Quantitative Genetics" as the general name of the there are complex genetic and epigenetic mechanisms third generation of quantitative genetics. Aylor and to the molecular regulation of the phenotypic charac- Zeng (2008) have also introduced the concept of sys- teristics of a trait at multiple levels, including DNA tems biology into quantitative genetics, in which a sequence variation, pre- and post- transcription framework was proposed to estimate and interpret events, pre- and post-translation processings, and the epistasis [25], but it involved the gene expression hierarchical or global gene network. It is now well traits rather than the macroscopic phenotype of bio- known that, from DNA to phenotype, the deletion, medically, economically, or evolutionarily important addition, substitution, covalent modification, alterna- traits. In our opinion, the systems quantitative genet- tive packaging of nucleotides, alternative splicing of ics is an interdisciplinary marriage of quantitative mRNAs, and even other kinds of soft inheritance genetics and systems biology. Historically inherited regulations widely participate in the process of han- from the classical and molecular quantitative genetics, dling genetic information [15]. Involving in both hard the systems quantitative genetics, following a new http://www.biolsci.org Int. J. Biol. Sci. 2009, 5 163 dynamic network model, could be defined as a new fast rate. It appears that the genetical genomics is now discipline that addresses the generalized genetic laws leading the frontier research of quantitative genetics of bioalleles
Load more

Recommended publications
  • Models of the Gene Must Inform Data-Mining Strategies in Genomics
    entropy Review Models of the Gene Must Inform Data-Mining Strategies in Genomics Łukasz Huminiecki Department of Molecular Biology, Institute of Genetics and Animal Biotechnology, Polish Academy of Sciences, 00-901 Warsaw, Poland; [email protected] Received: 13 July 2020; Accepted: 22 August 2020; Published: 27 August 2020 Abstract: The gene is a fundamental concept of genetics, which emerged with the Mendelian paradigm of heredity at the beginning of the 20th century. However, the concept has since diversified. Somewhat different narratives and models of the gene developed in several sub-disciplines of genetics, that is in classical genetics, population genetics, molecular genetics, genomics, and, recently, also, in systems genetics. Here, I ask how the diversity of the concept impacts data-integration and data-mining strategies for bioinformatics, genomics, statistical genetics, and data science. I also consider theoretical background of the concept of the gene in the ideas of empiricism and experimentalism, as well as reductionist and anti-reductionist narratives on the concept. Finally, a few strategies of analysis from published examples of data-mining projects are discussed. Moreover, the examples are re-interpreted in the light of the theoretical material. I argue that the choice of an optimal level of abstraction for the gene is vital for a successful genome analysis. Keywords: gene concept; scientific method; experimentalism; reductionism; anti-reductionism; data-mining 1. Introduction The gene is one of the most fundamental concepts in genetics (It is as important to biology, as the atom is to physics or the molecule to chemistry.). The concept was born with the Mendelian paradigm of heredity, and fundamentally influenced genetics over 150 years [1].
    [Show full text]
  • Special Issues on Advances in Quantitative Genetics: Introduction
    Heredity (2014) 112, 1–3 & 2014 Macmillan Publishers Limited All rights reserved 0018-067X/14 www.nature.com/hdy EDITORIAL Special issues on advances in quantitative genetics: introduction Heredity (2014) 112, 1–3; doi:10.1038/hdy.2013.115 Fisher’s (1918) classic paper on the inheritance of complex traits not While much of the focus was on standard biometrical applications only founded the field of quantitative genetics, but also coined the (for example, variance components), hints of things to come were term variance and introduced the powerful statistical method of foreshadowed by papers on the relevance of molecular biology to analysis of variance. This was a watershed paper, reconciling the breeding and applications of mixed models (models including both Mendelian’s discrete and saltatorial view of trait evolution with the fixed and random effects, for example, BLUP and REML). Much of gradual and continuous view of Darwin’s followers, the biometricians the emphasis was on breeding or laboratory populations. A decade (Provine, 1971). This fusion of Mendelian genetics with Darwinian later, the second ICQG held at Raleigh, North Carolina in 1987 natural selection was the start of the modern evolutionary synthesis. (Weir et al., 1988), reflected explosive growth in new tools (low- Fisher’s paper also marked a critical point in modern statistics, and density molecular markers for early quantitative trait locus (QTL) this synergism between the development of new statistical methods mapping), a continued expansion of the importance of mixed-model and the ever-increasing complexity of genetic/genomic data sets methodology for complex estimation issues, and a growing fusion of continues to this day.
    [Show full text]
  • New Strategies and Tools in Quantitative Genetics: How to Go from the Phenotype to the Genotype
    PP68CH16-Loudet ARI 6 April 2017 9:43 ANNUAL REVIEWS Further Click here to view this article's online features: • Download figures as PPT slides • Navigate linked references • Download citations New Strategies and Tools in • Explore related articles • Search keywords Quantitative Genetics: How to Go from the Phenotype to the Genotype Christos Bazakos, Mathieu Hanemian, Charlotte Trontin, JoseM.Jim´ enez-G´ omez,´ and Olivier Loudet Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Universite´ Paris-Saclay, 78026 Versailles Cedex, France; email: [email protected] Annu. Rev. Plant Biol. 2017. 68:435–55 Keywords First published online as a Review in Advance on genetic architecture, QTL, RIL, GWAS, phenotype February 6, 2017 The Annual Review of Plant Biology is online at Abstract plant.annualreviews.org Quantitative genetics has a long history in plants: It has been used to study https://doi.org/10.1146/annurev-arplant-042916- specific biological processes, identify the factors important for trait evolu- 040820 Annu. Rev. Plant Biol. 2017.68:435-455. Downloaded from www.annualreviews.org tion, and breed new crop varieties. These classical approaches to quantitative Copyright c 2017 by Annual Reviews. trait locus mapping have naturally improved with technology. In this review, All rights reserved we show how quantitative genetics has evolved recently in plants and how new developments in phenotyping, population generation, sequencing, gene Access provided by INRA Institut National de la Recherche Agronomique on 05/05/17. For personal use only. manipulation, and statistics are rejuvenating both the classical linkage map- ping approaches (for example, through nested association mapping) as well as the more recently developed genome-wide association studies.
    [Show full text]
  • Quantitative Genetics of Gene Expression and Methylation in the Chicken
    Andrey Höglund Linköping Studies In Science and Technology Dissertation No. 2097 FACULTY OF SCIENCE AND ENGINEERING Linköping Studies in Science and Technology, Dissertation No. 2097, 2020 Quantitative genetics Department of Physics, Chemistry and Biology Linköping University SE-581 83 Linköping, Sweden of gene expression Quantitative genetics of gene expression and methylation the in chicken www.liu.se and methylation in the chicken Andrey Höglund 2020 Linköping studies in science and technology, Dissertation No. 2097 Quantitative genetics of gene expression and methylation in the chicken Andrey Höglund IFM Biology Department of Physics, Chemistry and Biology Linköping University, SE-581 83, Linköping, Sweden Linköping 2020 Cover picture: Hanne Løvlie Cover illustration: Jan Sulocki During the course of the research underlying this thesis, Andrey Höglund was enrolled in Forum Scientium, a multidisciplinary doctoral program at Linköping University, Sweden. Linköping studies in science and technology, Dissertation No. 2097 Quantitative genetics of gene expression and methylation in the chicken Andrey Höglund ISSN: 0345-7524 ISBN: 978-91-7929-789-3 Printed in Sweden by LiU-tryck, Linköping, 2020 Abstract In quantitative genetics the relationship between genetic and phenotypic variation is investigated. The identification of these variants can bring improvements to selective breeding, allow for transgenic techniques to be applied in agricultural settings and assess the risk of polygenic diseases. To locate these variants, a linkage-based quantitative trait locus (QTL) approach can be applied. In this thesis, a chicken intercross population between wild and domestic birds have been used for QTL mapping of phenotypes such as comb, body and brain size, bone density and anxiety behaviour.
    [Show full text]
  • Epigenetics Is Normal Science, but Don't Call It Lamarckian
    Extended Abstract Volume 6:3, 2020 DOI: 6.2472/imedipce.2020.6.002 Journal of Clinical Epigenetics ISSN: 2472-1158 Open Access Epigenetics is Normal Science, But Don’t Call It Lamarckian David Penny New Zealand Extended Abstract they are general (but not necessarily universal) because they are found in Excavates, which many people consider are ancestral to other eukaryotes [6, 7]. Similarly, an important point is that Epigenetic mechanisms are increasingly being accepted as an integral methylation, phosphorylation, etc. of the DNA and of the histones is a part of normal science. Earlier genetic studies appear to have part of normal evolution (at least in eukaryotes that have the assumed that the only changes were ‘mutations’ as a result of a nucleosome structure) [8]. One of the most interesting aspects is change in the DNA sequence. If any such changes altered the amino methylation (and hydroxymethylation) of cytosine, and this is found in acid sequences then it was effectively a mutation, and if it occurred in many deep branching eukaryotes [9]. Typically there is methylation of a germline cell (including in unicellular organisms) then it could be cytosine molecules, especially in CpG (cytosine followed by guanine) passed on to subsequent generations. However, it is increasingly regions. The role of small RNAs in helping regulate the levels of apparent that other changes are also important, for example, changes protein expression is discussed in [10]. The main point here is that to methylation patterns, and to the histone proteins. Epigenetics was protein expression levels are very variable in all cells – it is not just sometimes consider ‘additional’ to classical genetics, but it is still fully classical genetics that is important; there are many epigenetic dependent on DNA, RNA and protein sequences, and at least since [1] mechanisms affecting the differences in protein expression.
    [Show full text]
  • Using Classical Genetics Simulator (CGS) to Teach Students the Basics of Genetic Research
    Tested Studies for Laboratory Teaching Proceedings of the Association for Biology Laboratory Education Vol. 33, 85–94, 2012 Using Classical Genetics Simulator (CGS) to Teach Students the Basics of Genetic Research Jean Heitz1, Mark Wolansky2, and Ben Adamczyk3 1University of Wisconsin, Zoology Department, 250 N. Mills Street, Madison WI 53706 USA 2University of Alberta, Department of Biological Science, Edmonton AB, CAN T6G 2E9 3Genedata, MA, A-1 Cranberry HI, Lexington MA 02421 USA ([email protected];[email protected];[email protected]) Some experiments are not well suited to large introductory labs because of space, time and funding constraints. Among these are classical Mendelian genetics investigations. Cyber labs can overcome these constraints. Classi- cal Genetics Simulator (CGS) gives students the opportunity to perform controlled crosses with model organisms much like a geneticist would do. CGS provides populations of Drosophila, Arabidopsis or mice with unknown patterns of inheritance and gives students the tools to design and perform experiments to discover these patterns. Students require an understanding of the what, why and how of solving genetic problems to successfully complete our cyber genetics lab activities. Keywords: Mendelian genetics, simulator, classical genetics simulator (CGS), linkage, monohybrid, dihybrid Introduction In large introductory biology classes some labs are dif- How can students get practice doing what geneticists ficult to do because of space, time and funding constraints. actually do? Among these are classical Mendelian genetics investiga- An obvious way for students to get practice doing what tions. As a result, we have turned to cyber labs. Working geneticists do is to conduct actual crosses.
    [Show full text]
  • An Introduction to Quantitative Genetics I Heather a Lawson Advanced Genetics Spring2018 Outline
    An Introduction to Quantitative Genetics I Heather A Lawson Advanced Genetics Spring2018 Outline • What is Quantitative Genetics? • Genotypic Values and Genetic Effects • Heritability • Linkage Disequilibrium and Genome-Wide Association Quantitative Genetics • The theory of the statistical relationship between genotypic variation and phenotypic variation. 1. What is the cause of phenotypic variation in natural populations? 2. What is the genetic architecture and molecular basis of phenotypic variation in natural populations? • Genotype • The genetic constitution of an organism or cell; also refers to the specific set of alleles inherited at a locus • Phenotype • Any measureable characteristic of an individual, such as height, arm length, test score, hair color, disease status, migration of proteins or DNA in a gel, etc. Nature Versus Nurture • Is a phenotype the result of genes or the environment? • False dichotomy • If NATURE: my genes made me do it! • If NURTURE: my mother made me do it! • The features of an organisms are due to an interaction of the individual’s genotype and environment Genetic Architecture: “sum” of the genetic effects upon a phenotype, including additive,dominance and parent-of-origin effects of several genes, pleiotropy and epistasis Different genetic architectures Different effects on the phenotype Types of Traits • Monogenic traits (rare) • Discrete binary characters • Modified by genetic and environmental background • Polygenic traits (common) • Discrete (e.g. bristle number on flies) or continuous (human height)
    [Show full text]
  • Quantitative Genetics and Heritability of Growth-Related Traits in Hybrid Striped Bass (Morone Chrysops ♀×Morone Saxatilis ♂)
    Aquaculture 261 (2006) 535–545 www.elsevier.com/locate/aqua-online Quantitative genetics and heritability of growth-related traits in hybrid striped bass (Morone chrysops ♀×Morone saxatilis ♂) Xiaoxue Wang a, Kirstin E. Ross b, Eric Saillant a, ⁎ Delbert M. Gatlin III a, John R. Gold a, a Center for Biosystematics and Biodiversity, Department of Wildlife and Fisheries Sciences, Texas A&M University, College Station, TX 77843-2258, USA b Department of Environmental Health, Flinders University, Adelaide, SA, 5001, Australia Received 30 November 2005; received in revised form 19 July 2006; accepted 21 July 2006 Abstract Commercially farmed, hybrid striped bass – female white bass (Morone chrysops) crossed with male striped bass (Morone saxatilis) – represent a rapidly growing industry in the United States. Expanded production of hybrid striped bass, however, is limited because of uncontrolled variation in performance of fish derived from undomesticated broodstock. A 10×10 factorial mating design was employed to examine genetic effects and heritability of growth-related traits based on dam half-sib and sire half- sib families. A total of 881 offspring were raised in a common environment and body weight and length were recorded at three different times post-fertilization; parentage of each fish was inferred from genotypes at 10 nuclear-encoded microsatellites. Dam and sire effects on juvenile growth (weight and length) and growth rate were significant, whereas dam by sire interaction effect was not. The dam and sire components of variance for weight and length (at age) and growth rate were estimated using a Restricted Maximum Likelihood algorithm. Estimates of broad-sense heritability of weight, using a family-mean basis, ranged from 0.67± 0.17 to 0.85±0.07 for dams; estimates for sires ranged from 0.43±0.20 to 0.77±0.10.
    [Show full text]
  • The Sustained Impact of Model Organisms—In Genetics and Epigenetics
    | COMMENTARY The Sustained Impact of Model Organisms—in Genetics and Epigenetics Nancy M. Bonini*,†,1 and Shelley L. Berger‡,1 *Department of Cellular and Developmental Biology, Perlman School of Medicine, †Department of Biology, and ‡Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania 19104 KEYWORDS classical genetics; epigenetics; behavior; genomics; human disease Now that DNA sequencing can reveal disease-relevant muta- The Rise of Model Organism Genetics and the tions in humans, it is appropriate to consider the history of Embrace of Molecular Genetics genetic research on model organisms, and whether model Model organism genetics has revealed many fundamental organisms will continue to play an important role. Our view is biological processes. This was achieved by applying unbiased that genetic research in model organisms has had an in- genetic screens to reveal genes and their mechanisms of disputably enormous impact on our understanding of com- action in processes such as cell cycle control (Nasmyth plex biological pathways and their epigenetic regulation, and 2001), basic body plan specification and mechanisms of de- on the development of tools and approaches that have been velopment (Lewis 1978; Nusslein-Volhard and Wieschaus crucial for studies of human biology. We submit that model 1980), and cell death pathways (Ellis and Horvitz 1986; organisms will remain indispensable for interpreting complex Avery and Horvitz 1987), all of which were recognized with genomic data, for testing hypotheses regarding function, and Nobel prizes. for further study of complex behaviors, to reveal not only The sequencing of genomes revealed the breadth of the novel genetic players, but also the profound impact of epige- conservation of genes, and of entire pathways.
    [Show full text]
  • Contribution and Perspectives of Quantitative Genetics to Plant Breeding in Brazil
    Contribution and perspectives of quantitative genetics to plant breeding in Brazil Crop Breeding and Applied Biotechnology S2: 7-14, 2012 Brazilian Society of Plant Breeding. Printed in Brazil Contribution and perspectives of quantitative genetics to plant breeding in Brazil Roland Vencovsky1, Magno Antonio Patto Ramalho2* and Fernando Henrique Ribeiro Barrozo Toledo1 Received 15 September 2012 Accepted 03 October 2012 Abstract – The purpose of this article is to show how quantitative genetics has contributed to the huge genetic progress obtained in plant breeding in Brazil in the last forty years. The information obtained through quantitative genetics has given Brazilian breeders the possibility of responding to innumerable questions in their work in a much more informative way, such as the use or not of hybrid cultivars, which segregating population to use, which breeding method to employ, alternatives for improving the efficiency of selec- tion programs, and how to handle the data of progeny and/or cultivars evaluations to identify the most stable ones and thus improve recommendations. Key words: Genetic parameters, genotype by environment interaction, hybrid cultivars, stability and adaptability. INTRODUCTION Therefore, this article was written up with the purpose of commenting some of the innumerable aspects of quantitative Plant breeding has been conceptualized in different genetics in Brazil that contributed to decision-making of manners throughout its history. In the concept proposed by breeders, creating good managers and, above all, showing Kempthorne (1957) “plant breeding is applied quantitative that in recent decades, many decisions of Brazilian breeders genetics.” Considering that he was a biometrician, it is easy have been based on knowledge from quantitative genetics.
    [Show full text]
  • Quantitative and Population Genetics
    Genome 371, 8 March 2010, Lecture 15 Quantitative and Population Genetics • What are quantitative traits and why do we care? - genetic basis of quantitative traits - heritability • Basic concepts of population genetics Final is Monday, March 15 8:30 a.m. Hogness Auditorium - in Health Sciences room A420 What Phenotypes/Diseases Do You Find Most Interesting? Quantitative Genetics • Concerned with the inheritance of differences between individuals that are a matter of degree rather than kind (i.e., quantitative not qualitative) Mice Fruit Flies In:Introduction to Quantitative Genetics Falconer & Mackay 1996 Many Discrete Traits Have an Underlying Quantitative Basis Serum Glucose Levels Some Puzzling Aspects of Quantitative Traits • Legendary debate in the early 1900’s on the genetic basis of quantitative traits -vs- “Mendelian” “Biometrician” • Genes are discrete and should lead to discrete phenotypes R- r r Sir Ronald Fisher To the Rescue 1918 paper “The Correlation Between Relatives on the Supposition of Mendelian Inheritance” reconciled this conflict Showed that inherently discontinuous variation caused by genetic segregation is translated into the continuous variation of quantitative characters Genetic Basis of Quantitative Traits First, we need a model: single locus with alleles A and a Familiar model Additive model one allele is dominant (uppercase) Active allele (uppercase) other allele is recessive (lowercase) Inactive allele (lower case) aa AA, Aa aa Aa AA 6 gms 14 gms 6 gms 10 gms 14 gms A General Additive Single Locus Model If
    [Show full text]
  • Quantitative Genetics.Pdf
    Conifer Translational Genomics Network Coordinated Agricultural Project Genomics in Tree Breeding and Forest Ecosystem Management ----- Module 4 – Quantitative Genetics Nicholas Wheeler & David Harry – Oregon State University www.pinegenome.org/ctgn Quantitative genetics . “Quantitative genetics is concerned with the inheritance of those differences between individuals that are of degree rather than of kind, quantitative rather than qualitative.” Falconer and MacKay, 1996 . Addresses traits such as – Growth, survival, reproductive ability – Cold hardiness, drought hardiness – Wood quality, disease resistance – Economic traits! Adaptive traits! Applied and evolutionary . Genetic principles – Builds upon both Mendelian and population genetics – Not limited to traits influenced by only one or a few genes – Analysis encompasses traits affected by many genes www.pinegenome.org/ctgn Height in humans is a quantitative trait Students from the University of Connecticut line up by height: 5’0” to 6’5” in 1” increments. Women are in white, men are in blue Figure Credit: Reproduced with permission of the Genetics Society of America, from [Birth defects, jimsonweed and bell curves, J.C. Crow, Genetics 147, 1997]; permission conveyed through Copyright Clearance Center, Inc. www.pinegenome.org/ctgn Quantitative genetics . Describes genetic variation based on phenotypic resemblance among relatives . Is usually the primary genetic tool for plant and animal breeding . Provides the basis for evaluating the relative genetic merit of potential parents . Provides tools for predicting response to selection (genetic gain) . How can we explain the continuous variation of metrical traits in terms of the discontinuous categories of Mendelian inheritance? – Simultaneous segregation of many genes – Non-genetic or environmental variation (truly continuous effects) www.pinegenome.org/ctgn Kernel Color in Wheat: Nilsson-Ehle www.pinegenome.org/ctgn 5 Consider a trait influenced by three loci The number of 'upper-case' alleles (black dots) behave as unit doses.
    [Show full text]